Grant: Doctoral Research Award: Canada Graduate Scholarships

Tailoring treatment to an individual's genetic profile through precision oncology has played an increasing role in cancer treatment over the last decade. Research has shown that there is value in approaching cancer on a case-by-case basis. However, this approach is labour intensive, requiring the interpretation of genomic results for each patient. Interpretation is currently one of the most significant bottlenecks during analysis due to the volume of data and the expertise needed to extract meaning from the results. Furthermore, results are difficult to translate into something concurrently meaningful for both patients and treating clinicians. Expert analysis and interpretation of a single patient may take several days, hampering the ability to transition precision oncology from research into the clinic and as a standard of care. This proposal aims to use natural language processing to create succinct and informative text summary interpretations for a given patient, which will support expert analysis. Summaries will be tailored to three audience groups: researchers and geneticists, clinicians and clinical nurses, and the general public representing the patients themselves. This will save time in analysis, improve consistency across centres, and provide an accessible format for the comprehension of genomic data.